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 针对支持向量机用于高光谱遥感影像分类存在的分类精度不高、参数选择困难等问题,提出一种再生核Hilbert空间的小波核。其可以逼近任意非线性函数,能够有效改进参数估计的效果,进而实现基于再生核Hilbert空间的小波核函数支持向量机(小波支持向量机)。并选取北京昌平地区的国产高光谱数据operational modular imaging spec-trometer II(OMIS II)和意大利Pavia大学ROSIS高光谱数据进行试验。结果表明,应用Coiflet小波核函数时能获得较高分类精度。 更多还原

【Abstract】 Some limitations exist in hyperspectral remote sensing image classification by SVM(support vector machine),such as unsatisfactory classification accuracy,difficult kernel parameter selection process and depen-dence on artificial tricks.In order to solve those problems,the wavelet SVM(WSVM) was proposed based on the investigation to SVM theory,reproducing kernel Hilbert space(RKHS) and the wavelet analysis.The wavelet kernel in RKHS can approximate arbitrary nonlinear functions and effectively ha... 更多还原